Advances in Applied Probability
Discrete-time risk-aware optimal switching with non-adapted costs
We solve non-Markovian optimal switching problems in discrete time on an infinite horizon, when the decision-maker is risk-aware and the filtration is general, and establish existence and uniqueness of solutions for the associated reflected backward st…
Advances in Applied Probability
Nash equilibrium structure of Cox process Hotelling games
We study an N-player game where a pure action of each player is to select a nonnegative function on a Polish space supporting a finite diffuse measure, subject to a finite constraint on the integral of the function. This function is used to define the …
Advances in Applied Probability
Limit theorems for continuous-state branching processes with immigration
A continuous-state branching process with immigration having branching mechanism and immigration mechanism , a CBI process for short, may have either of two different asymptotic regimes, depending on whether or . When , the CBI process has either a l…
Advances in Applied Probability
On operator fractional Lévy motion: integral representations and time-reversibility
In this paper, we construct operator fractional Lévy motion (ofLm), a broad class of infinitely divisible stochastic processes that are covariance operator self-similar and have wide-sense stationary increments. The ofLm class generalizes the univariat…
Advances in Applied Probability
Normal Approximation for Functions of Hidden Markov Models
The generalized perturbative approach is an all-purpose variant of Stein’s method used to obtain rates of normal approximation. Originally developed for functions of independent random variables, this method is here extended to functions of the realiza…
Advances in Applied Probability
On equal-input and monotone Markov matrices
The practically important classes of equal-input and of monotone Markov matrices are revisited, with special focus on embeddability, infinite divisibility, and mutual relations. Several uniqueness results for the classic Markov embedding problem are ob…
Advances in Applied Probability
Moment-constrained optimal dividends: precommitment and consistent planning
A moment constraint that limits the number of dividends in an optimal dividend problem is suggested. This leads to a new type of time-inconsistent stochastic impulse control problem. First, the optimal solution in the precommitment sense is derived. Se…
Advances in Applied Probability
On a random search tree: asymptotic enumeration of vertices by distance from leaves – CORRIGENDUM
We correct typographical errors in our original paper.
Advances in Applied Probability
An ephemerally self-exciting point process
Across a wide variety of applications, the self-exciting Hawkes process has been used to model phenomena in which the history of events influences future occurrences. However, there may be many situations in which the past events only influence the fut…